Add microbenchmark for layer normalization and improve latency#22223
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amarin16 merged 36 commits intomicrosoft:mainfrom Oct 15, 2024
Merged
Add microbenchmark for layer normalization and improve latency#22223amarin16 merged 36 commits intomicrosoft:mainfrom
amarin16 merged 36 commits intomicrosoft:mainfrom
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This reverts commit 6aece95.
Contributor
|
please add a summary of benchmark results. before vs. after |
fajin-corp
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Oct 11, 2024
fajin-corp
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Oct 11, 2024
fajin-corp
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Oct 11, 2024
fajin-corp
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Oct 11, 2024
fajin-corp
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Oct 11, 2024
Contributor
|
instead of converting fp16 to fp32, do you plan to implement fp16 kernels? |
Contributor
Author
that can be done in a separate PR |
fajin-corp
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Oct 14, 2024
fajin-corp
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fs-eire
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Oct 18, 2024
### Description The recent PR #22223 introduced 2 bugs in implementation of CPU LayerNorm f16: - possible access to nullptr for bias `const TensorShape& bias_shape = bias->Shape();` will crash when `bias` does not exist. (amazingly seems this one is not coverred by any test case) - fix: guard with pointer check - a racing condition inside ComputeJob `ComputeJob()` is dispatched to threadpool and it internally tries to modify `LayerNormImpl::scale_fp32_` and `LayerNormImpl::bias_fp32_`, which are `std::unique_ptr`s and are not thread-safe. - fix: move the modification of `LayerNormImpl::scale_fp32_` and `LayerNormImpl::bias_fp32_` out of `ComputeJob()` and put into `LayerNormImpl::ComputeWithoutContext()`. It may still have racing condition because `ConcurrentRunSupported` is set to `true` for CPU EP. Added an OrtMutex. This should fixes the recent flaky tests as well.
guschmue
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Oct 18, 2024
- Added a microbenchmark for the `LayerNormalization` MLFloat16 support added in #22063. - Updated the `LayerNormalization` MLFloat16 implementation to improve the latency. ``` ---------------------------------------------------------------------------------------------- Original MLFloat16 support Time CPU Iterations ---------------------------------------------------------------------------------------------- BM_LayerNormalization<MLFloat16, float>/1/real_time 15599 us 15625 us 47 BM_LayerNormalization<MLFloat16, float>/1/real_time 14714 us 14824 us 39 BM_LayerNormalization<MLFloat16, float>/1/real_time 14634 us 14688 us 50 ---------------------------------------------------------------------------------------------- Updated MLFloat16 support Time CPU Iterations ---------------------------------------------------------------------------------------------- BM_LayerNormalization<MLFloat16, float>/1/real_time 7276 us 7254 us 84 BM_LayerNormalization<MLFloat16, float>/1/real_time 6820 us 6720 us 93 BM_LayerNormalization<MLFloat16, float>/1/real_time 6840 us 6882 us 84 ```
guschmue
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Oct 18, 2024
### Description The recent PR #22223 introduced 2 bugs in implementation of CPU LayerNorm f16: - possible access to nullptr for bias `const TensorShape& bias_shape = bias->Shape();` will crash when `bias` does not exist. (amazingly seems this one is not coverred by any test case) - fix: guard with pointer check - a racing condition inside ComputeJob `ComputeJob()` is dispatched to threadpool and it internally tries to modify `LayerNormImpl::scale_fp32_` and `LayerNormImpl::bias_fp32_`, which are `std::unique_ptr`s and are not thread-safe. - fix: move the modification of `LayerNormImpl::scale_fp32_` and `LayerNormImpl::bias_fp32_` out of `ComputeJob()` and put into `LayerNormImpl::ComputeWithoutContext()`. It may still have racing condition because `ConcurrentRunSupported` is set to `true` for CPU EP. Added an OrtMutex. This should fixes the recent flaky tests as well.
tianleiwu
pushed a commit
that referenced
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Oct 18, 2024
### Description The recent PR #22223 introduced 2 bugs in implementation of CPU LayerNorm f16: - possible access to nullptr for bias `const TensorShape& bias_shape = bias->Shape();` will crash when `bias` does not exist. (amazingly seems this one is not coverred by any test case) - fix: guard with pointer check - a racing condition inside ComputeJob `ComputeJob()` is dispatched to threadpool and it internally tries to modify `LayerNormImpl::scale_fp32_` and `LayerNormImpl::bias_fp32_`, which are `std::unique_ptr`s and are not thread-safe. - fix: move the modification of `LayerNormImpl::scale_fp32_` and `LayerNormImpl::bias_fp32_` out of `ComputeJob()` and put into `LayerNormImpl::ComputeWithoutContext()`. It may still have racing condition because `ConcurrentRunSupported` is set to `true` for CPU EP. Added an OrtMutex. This should fixes the recent flaky tests as well.
apsonawane
pushed a commit
that referenced
this pull request
Oct 22, 2024
### Description The recent PR #22223 introduced 2 bugs in implementation of CPU LayerNorm f16: - possible access to nullptr for bias `const TensorShape& bias_shape = bias->Shape();` will crash when `bias` does not exist. (amazingly seems this one is not coverred by any test case) - fix: guard with pointer check - a racing condition inside ComputeJob `ComputeJob()` is dispatched to threadpool and it internally tries to modify `LayerNormImpl::scale_fp32_` and `LayerNormImpl::bias_fp32_`, which are `std::unique_ptr`s and are not thread-safe. - fix: move the modification of `LayerNormImpl::scale_fp32_` and `LayerNormImpl::bias_fp32_` out of `ComputeJob()` and put into `LayerNormImpl::ComputeWithoutContext()`. It may still have racing condition because `ConcurrentRunSupported` is set to `true` for CPU EP. Added an OrtMutex. This should fixes the recent flaky tests as well.
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LayerNormalizationMLFloat16 support added in Add MLFloat16 support for LayerNormalization, SkipLayerNormalization #22063.LayerNormalizationMLFloat16 implementation to improve the latency.